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Scale AI | Company Profile - Revenue, Headcount, Tech Stack, Contacts

Company Directory for Scale AI

Team Bitscale

— 2 min read

Scale AI

Overview

Scale AI is a data infrastructure company specializing in providing high-quality training data and advanced technologies for AI model development and deployment. Since its founding in 2016 by Alexandr Wang and Lucy Guo, Scale AI has evolved from a data annotation startup to a comprehensive "data foundry," serving enterprises, governments, and AI labs across multiple sectors.

Offering human-powered data labeling, annotation, RLHF technology, and end-to-end machine learning lifecycle management, Scale AI develops specialized AI agents and delivers full-stack data solutions for overseeing AI applications. The company focuses on delivering accurately labeled datasets to boost the effectiveness of machine learning models and has established partnerships with organizations like Meta, Microsoft, and OpenAI. Notable milestones include projected revenues of $2 billion for 2025 and a valuation of over $29 billion.

Basic Information

Industryinformation technology & services
Founded2016
Revenue870M
Headquarters303 2nd St, South Tower, 5th FL, San Francisco, California 94107, US
Alexa Ranking116158

Contact Details

Key Focus Areas & Initiatives

  • Computer vision
  • Data annotation
  • Sensor fusion
  • Machine learning
  • Autonomous driving
  • APIs
  • Ground truth data
  • Training data
  • Deep learning
  • Robotics
  • Drones
  • NLP
  • Document processing
  • Developer tools
  • Business process outsourcing
  • Enterprise software
  • Artificial intelligence
  • Model evaluation tools
  • Model deployment automation
  • AI data pipeline
  • Human-in-the-loop
  • AI model fine-tuning
  • Large language models (LLMs)
  • AI enterprise solutions
  • AI research
  • AI model evaluation benchmarks
  • AI industry partnerships
  • AI safety standards
  • Generative AI
  • Data quality assurance
  • AI for government
  • AI for defense
  • Data curation
  • AI deployment
  • ML lifecycle management
  • Custom AI models
  • Foundation models
  • AI safety and alignment
  • Reinforcement learning from human feedback (RLHF)
  • Data processing and hosting services
  • Model benchmarking
  • AI model security and compliance
  • Enterprise data integration

Technologies Used

  • AI
  • ANGEL LMS
  • AWS CloudFormation
  • AWS Transfer for SFTP
  • AWS Trusted Advisor
  • Act!
  • Ad Astra
  • Air
  • Amazon AWS
  • Amazon Web Services (AWS)
  • Android
  • Argon CI/CD Security
  • Atlassian Cloud
  • Azure Data Lake Storage
  • C#
  • CallMiner Eureka
  • CircleCI
  • Clari
  • CloudFlare Hosting
  • Cloudflare DNS
  • Data Analytics
  • Digital Ocean Spaces
  • Docker
  • Elasticsearch
  • FUSION
  • Fastapi
  • Flask
  • GCC
  • GitHub Actions
  • Gmail
  • Google Apps
  • Google Cloud Platform
  • Hubspot
  • IBM ILOG CPLEX Optimization Studio
  • Jamf
  • Javascript
  • Jira
  • Jira Service Management
  • Kubernetes
  • Mag+
  • Microsoft Azure
  • Microsoft Azure Monitor
  • Microsoft Office 365
  • Mode
  • MongoDB
  • Next.js
  • NumPy
  • Okta
  • OneTrust
  • PostgreSQL
  • Python
  • React
  • Remote
  • Repl.it
  • Retool
  • Route 53
  • SQL
  • Salesforce
  • Sendgrid
  • Slack
  • Snyk Code (SAST)
  • Tailwind
  • Temporal Cloud
  • Terraform
  • Tor
  • TypeScript
  • Vercel
  • Visio
  • Zapier
  • Zendesk
  • Zoho CRM
  • Zoom Rooms
  • pandas

Affiliated Organizations & Regional Branches

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